Ranking contemporary American poems

In this paper I use computational linguistics to find the differences between poems written by amateurs and poems written by professionals. I identify a number of linguistic variables that are important in distinguishing between the two classes of poems. To a large extent the findings corroborate those of earlier researchers, such as the fact that professional poems have more concrete language than amateur poems. However, I go on to use the identifed characteristics to create an ensemble classifier using the principles of machine learning. The holdout sample classification accuracy of the classifier is 80%. Furthermore, I go on to use the scores generated by the classifier to rank a number of contemporary American poets on a continuum from "amateur" to "professional". This method could be used by publishers to run an initial check on submitted poems to determine their merit

Modern perception of images created in Walt Whitman’s „Song of myself“, section 6

https://www.ester.ee/record=b5238364*es

Predicting the Quality of Short Narratives from Social Media

An important and difficult challenge in building computational models for narratives is the automatic evaluation of narrative quality. Quality evaluation connects narrative understanding and generation as generation systems need to evaluate their own products. To circumvent difficulties in acquiring annotations, we employ upvotes in social media as an approximate measure for story quality. We collected 54,484 answers from a crowd-powered question-and-answer website, Quora, and then used active learning to build a classifier that labeled 28,320 answers as stories. To predict the number of upvotes without the use of social network features, we create neural networks that model textual regions and the interdependence among regions, which serve as strong benchmarks for future research. To our best knowledge, this is the first large-scale study for automatic evaluation of narrative quality.Comment: 7 pages, 2 figures. Accepted at the 2017 IJCAI conferenc

Influence of Associations on the Reception of Poetry

Reading and understanding poetic texts is often described as an interactive process influenced by the words and phrases building the poems and all associations and images induced by them in the readers mind. Iser, for example, described the understanding process as the closing of a Good Gestalt promoted by mental images. Here we investigate the effect that semantic cohesion, that is the internal connection of a list words, has on understanding and appreciation of poetic texts. To do this word lists are presented as modern micropoems to the participants and the (ease of) extraction of underlying concepts as well as the affective and aesthetic responses are implicitly and explicitly measured. We found that a unifying concept is found more easily and unifying concepts vary significantly less between participants when the words composing a micropoem are semantically related. Moreover these items are liked better and are understood more easily. Our study shows evidence for the assumed relationship between building spontaneous associations, forming mental imagery, and understanding and appreciation of poetic texts. In addition, we introduced a new method well suited to manipulate backgrounding features independently of foregrounding features which allows to disentangle the effects of both on poetry reception

Invisible Net

In the past, several studies have found empirical support for the psychological notion of foregrounding. In this paper we will present the results of a reading experiment investigating descriptive and evaluative reader reactions to a poem, both in its original form (containing rather heavy foregrounding, both deviation and parallelism) and a version (from which all foregrounding has been removed). In this sense the research presents a replication of earlier experiments as well as a comparison with some more recent ones that failed to find empirical evidence for the notion of foregrounding. It will also cast light on Bortolussi and Dixon’s rereading paradigm. The results will be combined with a reconsideration of the concept of literariness, which will be confronted with the variety within a reader population, as well as with the diversity within a text corpus. The latter will be confronted with Van Peer’s (1991) effort to develop a descriptive definition of literature, incorporating the heterogeneous nature of the corpus of texts that are regarded as literary. Revisiting these aspects of texts and their reception may illuminate persistent problems in the theory of literariness

#does this count as poetry? : A genre analysis of Tumblr poetry

This thesis canonizes “Tumblr poetry” as a distinct and separate genre of poetry, closely related to other digital poetry movements but ultimately its own phenomenon. Through historical analysis, the criticism against Tumblr poetry and digital poetry as a whole become familiar in a cycle of negative reactions to changing poets and changing audiences. Through textual analysis of poems found on Tumblr, common attributes and style changes are identified and contrasted with more traditional contemporary poetry, signifying a distinct formal shift. Finally, through a platform analysis, poetry communities on Reddit and Instagram are similarly analyzed and contrasted with Tumblr poetry to showcase the effects that platform has on the communities that form, and why “Tumblr poetry” is not the same as “internet poetry.” Through these three different analyses, a more rounded image of Tumblr poetry as a phenomenon becomes apparent, further contributing to research about how community and art creation interact, and how digital culture and “mainstream” culture are becoming more ubiquitous

The Gutenberg English Poetry Corpus: Exemplary Quantitative Narrative Analyses

This paper describes a corpus of about 3,000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative narrative analysis (QNA) is used to explore a cleaned subcorpus, the Gutenberg English Poetry Corpus (GEPC), which comprises over 100 poetic texts with around two million words from about 50 authors (e.g., Keats, Joyce, Wordsworth). Some exemplary QNA studies show author similarities based on latent semantic analysis, significant topics for each author or various text-analytic metrics for George Eliot’s poem “How Lisa Loved the King” and James Joyce’s “Chamber Music,” concerning, e.g., lexical diversity or sentiment analysis. The GEPC is particularly suited for research in Digital Humanities, Computational Stylistics, or Neurocognitive Poetics, e.g., as training and test corpus for stimulus development and control in empirical studies

Visualizing Words and Knowledge: Arts of Memory from the Agora to the Computer

This dissertation examines rhetoric\u27s fourth canon--the art of memory--tracing its development through the classical, medieval, and early modern periods. It argues that for most of its history, the fourth canon was an art by which words and knowledge were remediated into visual, spatial forms, either in the mind or on the page. And it was this technique of visualization, I argue, that linked the canons of memory and invention throughout history. In contemporary rhetorical theory, however, memory palaces and mnemonic imagery have been replaced with a conception of memory grounded in psychology and critique. I argue that this move away from memory as an artificial practice has obscured the classical art\u27s visual precepts, consequently severing the ancient link between memory and invention. I suggest that contemporary rhetorical theorists should return to visualization to revitalize the fourth canon in the twenty-first century. Today, digital tools that visualize words and knowledge are ubiquitous. Framing data visualization as a twenty-first century analogue to the art of memory allows us to think about visualization as a tool for invention rather than as a reified representation of data. As creative remediations, memory palaces once allowed rhetoricians to interface with knowledge in an adaptable way and to imagine how knowledge might be assembled together in a new discourse. Thinking about data visualization as a memory palace thus enables us to think not only about representing data but about the new ways we might interface with it in order to generate insight. Data visualization becomes an art to facilitate invention, as the classical art of memory was designed to do